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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

An application example is a session store recording recent actions. Application example: photo tagging; add a tag is an update, but most operations are to read tags. Application example: user profile cache, where profiles are constructed elsewhere (e.g., Run phase is where each db is tested for different test conditions.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. Cache Hit Ratio The cache hit ratio represents the efficiency of cache usage.

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Why Tcl is 700% faster than Python for database benchmarking

HammerDB

Python is a popular programming language, especially for beginners, and consequently we see it occurring in places where it just shouldn’t be used, such as database benchmarking. We use stored procedures because, as the introductory post shows, using single SQL statements turns our database benchmark into a network test).

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Measure What You Impact, Not What You Influence

CSS Wizardry

Most metrics are not atomic: FCP, for example, isn’t a metric we can optimise in isolation—it’s a culmination of other more atomic metrics such as connection overhead, TTFB, and more. For the sake of ease, I’m going to use Largest Contentful Paint (LCP) as the example. For example, continuing our task to reduce CSS size: performance.

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How to use Server Timing to get backend transparency from your CDN

Speed Curve

Looking at the industry benchmarks for US retailers , four well-known sites have backend times that are approaching – or well beyond – that threshold. Pagespeed Benchmarks - US Retail - LCP When you examine a waterfall, it's pretty obvious that TTFB is the long pole in the tent, pushing out render times for the page.

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View from Nutanix storage during Postgres DB benchmark

n0derunner

In this example from prior post. Since the DB is small (50% the size of the Linux RAM) – the database is mostly cached on the read side – so we only see writes going to the DB files. The post View from Nutanix storage during Postgres DB benchmark appeared first on n0derunner.

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Evaluating the Evaluation: A Benchmarking Checklist

Brendan Gregg

These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Accurate benchmarking rewards engineering investment that actually improves performance, but, unfortunately, inaccurate benchmarking is more common. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?